Sensing and modeling social networks within an organization can be of benefit to enhance productivity and workplace happiness. Specifically, researchers look to capture phone, email, or other virtual means of communication in an effort to develop a complete model of a human network. Using a data-driven research approach, researchers can understand how communication networks function in an organization.
But, attempting to capture the interactions of numerous members of a larger organization can be difficult, if not seemingly impossible. Typically, many researchers are limited to studying the interactions of only a few users, with many of these interactions requiring subjective input from the users that may ultimately affect the data. To overcome the bottleneck of the number of people that can be surveyed in a human behavioral research study, various organizations have proposed using a wearable computer to gather information from a larger number of users.
The wearable computers generally rely on infrared transmission and are large and noticeable amongst others within the communication network. Additionally, certain wearable computers require the user to input subjective measures of how the user felt during certain interactions (i.e., the user felt the interaction went well, the user felt the interaction went poorly). Naturally, these shortcomings introduce numerous potential errors for researchers studying human behavior within an organization.